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A membrane assisted process for green hydrogen production from a bioethanol derived feedstock is here developed and evaluated, starting from the conventional Steam Methane Reforming (SMR) process. Such a process is suitable for centralized hydrogen production, and is here analyzed for a large-scale H2 production unit with the capacity of 40.000 Nm3/h. The basic Steam Ethanol Reforming (SER) process scheme is modified in a membrane assisted process by integrating the Pd-membrane separation steps in the most suitable reaction steps. The membrane assisted process, configured in three alternative architectures (Open architecture, Membrane Reactor and Hybrid architecture) was evaluated in terms of efficiencies and hydrogen yields, obtaining a clear indication of improved process performance. The alternative membrane assisted process architectures are compared to the basic SER process and to the benchmark SMR process fed by natural gas, for an overall comparative assessment of the efficiency and specific CO2 emissions and for an economic analysis based on the operating expenditures.

A membrane assisted process for green hydrogen production from a bioethanol derived feedstock is here developed and evaluated, starting from the conventional Steam Methane Reforming (SMR) process. Such a process is suitable for centralized hydrogen production, and is here analyzed for a large-scale H2 production unit with the capacity of 40.000 Nm3/h. The basic Steam Ethanol Reforming (SER) process scheme is modified in a membrane assisted process by integrating the Pd-membrane separation steps in the most suitable reaction steps. The membrane assisted process, configured in three alternative architectures (Open architecture, Membrane Reactor and Hybrid architecture) was evaluated in terms of efficiencies and hydrogen yields, obtaining a clear indication of improved process performance. The alternative membrane assisted process architectures are compared to the basic SER process and to the benchmark SMR process fed by natural gas, for an overall comparative assessment of the efficiency and specific CO2 emissions and for an economic analysis based on the operating expenditures.

Abstract The upward energy demand, along with the depletion of conventional energy sources, demands improved utilization of renewable energy resources. Among all renewable energy resources, solar energy is the most appropriate alternative to conventional energy sources owing to its inexhaustibility and green property. Solar collectors are devices that convert solar radiation into heat or energy. However, the efficiency of the solar collector is still not adequate. The competent step to enhance the efficiency of the solar collector is to use nanofluids. This study is carried out different phases viz. characterization and stabilization while both qualitative and quantitative methods used to evaluate the stability of nanofluids thermophysical properties of Al2O3 and CNC nanofluids such as thermal conductivity measured at four different temperature using KD2 Pro, viscosity and specific heat determined at similar temperature range by viscometer and differential scanning calorimetry respectively. The experiment is executed with a fixed flow rate and in steady-state conditions under extensive solar radiation. The experimental study has revealed that up to 2.48% and 8.46% efficiency of solar collector enhanced by using 0.5% Al2O3 and 0.5% CNC nanofluids respectively. Moreover, nanofluids show good to moderate stability performance. Besides, the thermal conductivity of nanofluids increased while viscosity is in a decreasing trend with increasing temperature. Nanofluids could enhance the efficiency of a flat-plate solar collector.

Abstract The upward energy demand, along with the depletion of conventional energy sources, demands improved utilization of renewable energy resources. Among all renewable energy resources, solar energy is the most appropriate alternative to conventional energy sources owing to its inexhaustibility and green property. Solar collectors are devices that convert solar radiation into heat or energy. However, the efficiency of the solar collector is still not adequate. The competent step to enhance the efficiency of the solar collector is to use nanofluids. This study is carried out different phases viz. characterization and stabilization while both qualitative and quantitative methods used to evaluate the stability of nanofluids thermophysical properties of Al2O3 and CNC nanofluids such as thermal conductivity measured at four different temperature using KD2 Pro, viscosity and specific heat determined at similar temperature range by viscometer and differential scanning calorimetry respectively. The experiment is executed with a fixed flow rate and in steady-state conditions under extensive solar radiation. The experimental study has revealed that up to 2.48% and 8.46% efficiency of solar collector enhanced by using 0.5% Al2O3 and 0.5% CNC nanofluids respectively. Moreover, nanofluids show good to moderate stability performance. Besides, the thermal conductivity of nanofluids increased while viscosity is in a decreasing trend with increasing temperature. Nanofluids could enhance the efficiency of a flat-plate solar collector.

Co-generation of energy derived from human movement is not new. Intentionally accumulating energy, from mass urban-mobility, provides opportunities to re-purpose power. However, when mass-mobility is predictable, yet not harnessed, this highlights critical gaps in application of interdisciplinary knowledge. This research highlights a novel application of geostatistical modelling for the built environment with the purpose of understanding where energy harvesting infrastructure should be located. The work presented argues that advanced Geostatistical methods can be implemented as an appropriate method to predict probability distribution, density, clustering of populations and mass-population mobility patterns from large-scale online distributed and heterogeneous data sets published by the Australian Urban Research Infrastructure Network. Where clear urban spatio-behavioural relationships of density and movement can be predicted – understanding such patterns supports cross-disciplinary city planning and decision-making. A data-informed – predictive spatial decision-making framework is proposed – facilitating the endeavour of cogenerating kinetic human energy within a prescribed space. This novel proposition could further sustainability strategies for compact living for cities such as in Perth, Western Australia which is increasingly economically and geographically pressured to densify. This research argues that surveillance data elucidate a capacity to interpret and understand impacts of densification strategies, efficacy of CCTV networks in existing and emerging cities.

Co-generation of energy derived from human movement is not new. Intentionally accumulating energy, from mass urban-mobility, provides opportunities to re-purpose power. However, when mass-mobility is predictable, yet not harnessed, this highlights critical gaps in application of interdisciplinary knowledge. This research highlights a novel application of geostatistical modelling for the built environment with the purpose of understanding where energy harvesting infrastructure should be located. The work presented argues that advanced Geostatistical methods can be implemented as an appropriate method to predict probability distribution, density, clustering of populations and mass-population mobility patterns from large-scale online distributed and heterogeneous data sets published by the Australian Urban Research Infrastructure Network. Where clear urban spatio-behavioural relationships of density and movement can be predicted – understanding such patterns supports cross-disciplinary city planning and decision-making. A data-informed – predictive spatial decision-making framework is proposed – facilitating the endeavour of cogenerating kinetic human energy within a prescribed space. This novel proposition could further sustainability strategies for compact living for cities such as in Perth, Western Australia which is increasingly economically and geographically pressured to densify. This research argues that surveillance data elucidate a capacity to interpret and understand impacts of densification strategies, efficacy of CCTV networks in existing and emerging cities.

In the UK electricity market, generators are obliged to produce part of their electricity with renewable energy resources in accordance with the Renewable Obligation Order. Since 2009 technology banding has been added, meaning that different technologies are rewarded with a different number of certificates. We analyze these two different renewable obligation policies in a mathematical representation of an electricity market with random availabilities of renewable generation outputs and random electricity demand. We also present another, alternative, banding policy. We provide revenue adequate pricing schemes for the three obligation policies. We carry out a simulation study via sampling. A key finding is that the UK banding policy cannot guarantee that the original obligation target is met, hence potentially resulting in more pollution. Our alternative provides a way to make sure that the target is met while supporting less established technologies, but it comes with a significantly higher consumer price. Furthermore, as an undesirable side effect, we observe that a cost reduction in a technology with a high banding (namely offshore wind) leads to more CO2 emissions under the UK banding policy and to higher consumer prices under the alternative banding policy.